datasette/README.md

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# datasette
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*An instant JSON API for your SQLite databases*
Datasette provides an instant, read-only JSON API for any SQLite database. It also provides tools for packaging the database up as a Docker container and deploying that container to hosting providers such as [Zeit Now](https://zeit.co/now).
## Installation
pip3 install datasette
Datasette requires Python 3.5 or higher.
## Basic usage
datasette serve path/to/database.db
This will start a web server on port 8001 - visit http://localhost:8001/ to access the web interface.
`serve` is the default subcommand, you can omit it if you like.
Use Chrome on OS X? You can run datasette against your browser history like so:
datasette ~/Library/Application\ Support/Google/Chrome/Default/History
Now visiting http://localhost:8001/History/downloads will show you a web interface to browse your downloads data:
![Downloads table rendered by datasette](https://static.simonwillison.net/static/2017/datasette-downloads.png)
http://localhost:8001/History/downloads.json will return that data as JSON:
{
"database": "History",
"columns": [
"id",
"current_path",
"target_path",
"start_time",
"received_bytes",
"total_bytes",
...
],
"table_rows": 576,
"rows": [
[
1,
"/Users/simonw/Downloads/DropboxInstaller.dmg",
"/Users/simonw/Downloads/DropboxInstaller.dmg",
13097290269022132,
626688,
0,
...
]
]
}
http://localhost:8001/History/downloads.jsono will return that data as JSON in a more convenient but less efficient format:
{
...
"rows": [
{
"start_time": 13097290269022132,
"interrupt_reason": 0,
"hash": "",
"id": 1,
"site_url": "",
"referrer": "https://www.dropbox.com/downloading?src=index",
...
}
]
}
## datasette serve options
$ datasette serve --help
Usage: datasette serve [OPTIONS] [FILES]...
Serve up specified SQLite database files with a web UI
Options:
-h, --host TEXT host for server, defaults to 0.0.0.0
-p, --port INTEGER port for server, defaults to 8001
--debug Enable debug mode - useful for development
--reload Automatically reload if code change detected -
useful for development
--cors Enable CORS by serving Access-Control-Allow-
Origin: *
--page_size INTEGER Page size - default is 100
--max_returned_rows INTEGER Max allowed rows to return at once - default is
1000. Set to 0 to disable check entirely.
--inspect-file TEXT Path to JSON file created using "datasette
build"
-m, --metadata FILENAME Path to JSON file containing license/source
metadata
--help Show this message and exit.
## metadata.json
If you want to include licensing and source information in the generated datasette website you can do so using a JSON file that looks something like this:
{
"title": "Five Thirty Eight",
"license": "CC Attribution 4.0 License",
"license_url": "http://creativecommons.org/licenses/by/4.0/",
"source": "fivethirtyeight/data on GitHub",
"source_url": "https://github.com/fivethirtyeight/data"
}
The license and source information will be displayed on the index page and in the footer. They will also be included in the JSON produced by the API.
## datasette publish
If you have [Zeit Now](https://zeit.co/now) installed, datasette can deploy one or more SQLite databases to the internet with a single command:
datasette publish now database.db
This will create a docker image containing both the datasette application and the specified SQLite database files. It will then deploy that image to Zeit Now and give you a URL to access the API.
$ datasette publish --help
Usage: datasette publish [OPTIONS] PUBLISHER [FILES]...
Publish specified SQLite database files to the internet along with a
datasette API.
Only current option for PUBLISHER is 'now'. You must have Zeit Now
installed: https://zeit.co/now
Example usage: datasette publish now my-database.db
Options:
-n, --name TEXT Application name to use when deploying to Now
-m, --metadata FILENAME Path to JSON file containing metadata to publish
--help Show this message and exit.
## datasette package
If you have docker installed you can use `datasette package` to create a new Docker image in your local repository containing the datasette app and selected SQLite databases:
$ datasette package --help
Usage: datasette package [OPTIONS] FILES...
Package specified SQLite files into a new datasette Docker container
Options:
-t, --tag TEXT Name for the resulting Docker container, can
optionally use name:tag format
-m, --metadata FILENAME Path to JSON file containing metadata to publish
--help Show this message and exit.